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Ammonia pyrolysis oxidation excited by nanosecond pulsed discharge:Global/fluid models hybrid solution

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Journal of Energy Chemistry 2025年第1期100卷 385-396页

作者： Mingming Zhang Hanyu Wu Qi Chen Jiaxin Yang Bonan Liu School of Mechanical Electronic and Control Engineering Beijing Jiaotong University China University of Petroleum

The kinetic characteristics of plasma-assisted oxidative pyrolysis of ammonia are studied by using the global/fluid models hybrid solution ***,the stable products of plasma-assisted oxidative pyrolysis of ammonia are *** results show that the consumption of NH3/O2and the production of N2/H2change linearly with the increase of voltage,which indicates the decoupling of nonequilibrium molecular excitation and oxidative pyrolysis of ammonia at low ***,the detailed reaction kinetics mechanism of ammonia oxidative pyrolysis stimulated by a nanosecond pulse voltage at low pressure and room temperature is *** on the reaction path analysis,the simplified mechanism is *** detailed and simplified mechanism simulation results are compared with experimental data to verify the accuracy of the simplified ***,based on the simplified mechanism,the fluid model of ammonia oxidative pyrolysis stimulated by the nanosecond pulse plasma is established to study the pre-sheath/sheath behavior and the resultant consumption and formation of key *** results show that the generation,development,and propagation of the pre-sheath have a great influence on the formation and consumption of *** consumption of NH3by the cathode pre-sheath is greater than that by the anode pre-sheath,but the opposite is true for OH and O（1S）.However,within the sheath,almost all reactions do not ***,by changing the parameters of nanosecond pulse power supply voltage,it is found that the electron number density,electron current density,and applied peak voltages are not the direct reasons for the structural changes of the sheath and ***,the discharge interval has little effect on the sheath structure and gas mixture *** research results of this paper not only help to understand the kinetic promotion of non-equilibrium excitation in the process of oxidative pyrolysis but also help to explore th

关键词： Nanosecond pulsed discharge Ammonia Oxidative pyrolysis Fluid model Global model

Robust Backstepping Control of a Quadrotor Unmanned Aerial Vehicle under Colored Noises

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Computers, Materials & Continua 2025年第1期82卷 777-798页

作者： Mehmet Karahan Electrical and electronic engineering Department Atilim UniversityAnkara06830Turkey

Advances in software and hardware technologies have facilitated the production of quadrotor unmanned aerial vehicles(UAVs).Nowadays,people actively use quadrotor UAVs in essential missions such as search and rescue,counter-terrorism,firefighting,surveillance,and cargo *** performing these tasks,quadrotors must operate in noisy ***,a robust controller design that can control the altitude and attitude of the quadrotor in noisy environments is of great *** researchers have focused only on white Gaussian noise in their studies,whereas researchers need to consider the effects of all colored noises during the operation of the *** study aims to design a robust controller that is resistant to all colored ***,a nonlinear quadrotormodel was created with ***,a backstepping controller resistant to colored noises was *** backstepping controller was tested under Gaussian white,pink,brown,blue,and purple *** and Lyapunov-based controller designswere also carried out,and their time responses(rise time,overshoot,settling time)were compared with those of the backstepping *** the simulations,time was in seconds,altitude was in meters,and roll,pitch,and yaw references were in *** and settling time values were in seconds,and overshoot value was in *** the obtained values are examined,simulations prove that the proposed backstepping controller has the least overshoot and the shortest settling time under all noise types.

关键词： Backstepping control colored noises Gaussian noise Lyapunov stability quadrotor robustness PID control

Method for Estimating the State of Health of Lithium-ion Batteries Based on Differential Thermal Voltammetry and Sparrow Search Algorithm-Elman Neural Network

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Energy engineering 2025年第1期122卷 203-220页

作者： Yu Zhang Daoyu Zhang TiezhouWu School of Electrical and electronic engineering Hubei University of TechnologyWuhan430068China

Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery ***,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity ***,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model *** address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural ***,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity ***,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network *** validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging *** experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.

关键词： Lithium-ion battery state of health differential thermal voltammetry Sparrow Search Algorithm

An Improved Practical Byzantine Fault-Tolerant Algorithm Based on XGBoost Grouping for Consortium Chains

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Computers, Materials & Continua 2025年第1期82卷 1295-1311页

作者： Xiaowei Wang Haiyang Zhang Jiasheng Zhang Yingkai Ge Kexin Cui Zifu Peng Zhengyi Li Lihua Wang College of electronic and Information engineering Shandong University of Science and TechnologyQingdao266590China

In response to the challenges presented by the unreliable identity of the master node,high communication overhead,and limited network support size within the Practical Byzantine Fault-Tolerant(PBFT)algorithm for consortium chains,we propose an improved PBFT algorithm based on XGBoost grouping called XG-PBFT in this ***-PBFT constructs a dataset by training important parameters that affect node performance,which are used as classification indexes for *** XGBoost algorithm then is employed to train the dataset,and nodes joining the system will be grouped according to the trained grouping *** them,the nodes with higher parameter indexes will be assigned to the consensus group to participate in the consensus,and the rest of the nodes will be assigned to the general group to receive the consensus *** order to reduce the resource waste of the system,XG-PBFT optimizes the consensus protocol for the problem of high complexity of PBFT ***,we evaluate the performance of *** experimental results show that XG-PBFT can significantly improve the performance of throughput,consensus delay and communication complexity compared to the original PBFT algorithm,and the performance enhancement is significant compared to other algorithms in the case of a larger number of *** results demonstrate that the XG-PBFT algorithm is more suitable for large-scale consortium chains.

关键词： Consortium chain PBFT grouping reputation XGBoost

Distributed fiber optic sensing system for vibration monitoring of 3D printed bridges

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Optoelectronics Letters 2025年第1期21卷 28-34页

作者： ZHAO Shuai ZHOU Ran LUO Mingming LIU Jianfei LIU Xiongfei ZHOU Tao School of electronic Information engineering Hebei University of Technology Tianjin Key Laboratory of electronic Materials and Devices School of Civil engineering and Transportation Hebei University of Technology Tianjin Jinhang Institute of Technical Physics

The fiber optic sensing technology provides data support in structural health monitoring of the macro facilities, including design, construction, and maintenance of bridges, tunnels, ports and other infrastructures. In this paper, a distributed vibration sensing system is proved to be responsive to a single touch over a 1.8-m-long equivalent fiber segment, covering a vibration frequency from 5 Hz to 25 kHz. The sensing fiber was arranged as an S type layout on the bridge to recognize the standing state, windblown disturbance, and walking vibration. Moreover, the knocking and climbing events are recognized fiber laying spinning lines and hanging on the fences, respectively. The demonstration shows an accurate positioning and sensitive vibration monitoring applied on the automated three-dimensional(3D) printed bridge, which is applicable to all kinds of 3D printed facilities as intelligent sensory neuro-networks.

关键词： Spinning (fibers)

Construction of 3D porous Cu_(1.81)S/nitrogen-doped carbon frameworks for ultrafast and long-cycle life sodium-ion storage

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 191-200页

作者： Chen Chen Hongyu Xue Qilin Hu Mengfan Wang Pan Shang Ziyan Liu Tao Peng Deyang Zhang Yongsong Luo Key Laboratory of Microelectronics and Energy of Henan Province Henan Joint International Research Laboratory of New Energy Storage TechnologyCollege of Physics and Electronic EngineeringXinyang Normal UniversityXinyang 464000China School of Physics and electronic engineering Nanyang Normal UniversityNanyang 473061China

Transition metal sulfides have great potential as anode mterials for sodium-ion batteries(SIBs)due to their high theoretical specific ***,the inferior intrinsic conductivity and large volume variation during sodiation-desodiation processes seriously affect its high-rate and long-cyde performance,unbeneficial for the application as fast-charging and long-cycling SIBs ***,the three-dimensional porous Cu_(1.81)S/nitrogen-doped carbon frameworks(Cu_(1.81)S/NC)are synthesized by the simple and facile sol-gel and annealing processes,which can accommodate the volumetric expansion of Cu_(1.81)S nanoparticles and accelerate the transmission of ions and electrons during Na^(+)insertion/extraction processes,exhibiting the excellent rate capability(250.6 mA·g^(-1)at 20.0 A·g^(-1))and outstanding cycling stability(70% capacity retention for 6000 cycles at 10.0 A·g^(-1))for ***,the Na-ion full cells coupled with Na_(3)V_(2)(PO_(4))_(3)/C cathode also demonstrate the satisfactory reversible specific capacity of 330.5 mAh·g^(-1)at 5.0 A·g^(-1)and long-cycle performance with the 86.9% capacity retention at 2.0 A·g^(-1)after 750 *** work proposes a promising way for the conversionbased metal sulfides for the applications as fast-charging sodium-ion battery anode.

关键词： copper sulfide nanoparticles porous carbon framework fast charging long-cycle performance sodium-ion full batteries

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Industrial Control Anomaly Detection Based on Distributed Linear Deep Learning

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Computers, Materials & Continua 2025年第1期82卷 1129-1150页

作者： Shijie Tang Yong Ding Huiyong Wang School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin541004China School of electronic engineering and Automation Guilin University of Electronic TechnologyGuilin541004China Guangxi engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic TechnologyGuilin541004China Institute of Cyberspace Technology HKCT Institute for Higher EducationHong Kong999077China School of Mathematics&Computing Science Guilin University of Electronic TechnologyGuilin541004China

As more and more devices in Cyber-Physical Systems(CPS)are connected to the Internet,physical components such as programmable logic controller(PLC),sensors,and actuators are facing greater risks of network attacks,and fast and accurate attack detection techniques are *** key problem in distinguishing between normal and abnormal sequences is to model sequential changes in a large and diverse field of time *** address this issue,we propose an anomaly detection method based on distributed deep *** method uses a bilateral filtering algorithm for sequential sequences to remove noise in the time series,which can maintain the edge of discrete *** use a distributed linear deep learning model to establish a sequential prediction model and adjust the threshold for anomaly detection based on the prediction error of the validation *** method can not only detect abnormal attacks but also locate the sensors that cause *** conducted experiments on the Secure Water Treatment(SWAT)and Water Distribution(WADI)public *** experimental results show that our method is superior to the baseline method in identifying the types of attacks and detecting efficiency.

关键词： Anomaly detection CPS deep learning MLP(multi-layer perceptron)

Unlocking the stable interface in aqueous zinc-ion battery with multifunctional xylose-based electrolyte additives

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Journal of Energy Chemistry 2025年第1期100卷 770-778页

作者： Xiaoqin Li Jian Xiang Lu Qiu Xiaohan Chen Yinkun Zhao Yujue Wang Qu Yue Taotao Gao Wenlong Liu Dan Xiao Zhaoyu Jin Panpan Li Institute for Advanced Study Chengdu University School of Mechanical engineering Chengdu University College of Food and Biological engineering Chengdu University Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China College of Materials Science and engineering Sichuan University

The growth of dendrites and the side reactions occurring at the Zn anode pose significant challenges to the commercialization of aqueous Zn-ion batteries（AZIBs）. These challenges arise from the inherent conflict between mass transfer and electrochemical kinetics. In this study, we propose the use of a multifunctional electrolyte additive based on the xylose（Xylo） molecule to address these issues by modulating the solvation structure and electrode/electrolyte interface, thereby stabilizing the Zn anode. The introduction of the additive alters the solvation structure, creating steric hindrance that impedes charge transfer and then reduces electrochemical kinetics. Furthermore, in-situ analyses demonstrate that the reconstructed electrode/electrolyte interface facilitates stable and rapid Zn2+ion migration and suppresses corrosion and hydrogen evolution reactions. As a result, symmetric cells incorporating the Xylo additive exhibit significantly enhanced reversibility during the Zn plating/stripping process, with an impressively long lifespan of up to 1986 h, compared to cells using pure ZnSO4electrolyte. When combined with a polyaniline cathode, the full cells demonstrate improved capacity and long-term cyclic stability. This work offers an effective direction for improving the stability of Zn anode via electrolyte design, as well as highperformance AZIBs.

关键词： Solvation

A Generative Model-Based Network Framework for Ecological Data Reconstruction

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Computers, Materials & Continua 2025年第1期82卷 929-948页

作者： Shuqiao Liu Zhao Zhang Hongyan Zhou Xuebo Chen School of electronic and Information engineering University of Science and Technology LiaoningAnshan114051China School of Computer Science and Software engineering University of Science and Technology LiaoningAnshan114051China

This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection *** Strengths,Weaknesses,Opportunities,Threats(SWOT)analysis data with Variation Autoencoder(VAE)and Generative AdversarialNetwork(GAN)the network framework model(SAE-GAN),is proposed for environmental data *** model combines two popular generative models,GAN and VAE,to generate features conditional on categorical data embedding after SWOT *** model is capable of generating features that resemble real feature distributions and adding sample factors to more accurately track individual sample *** data is used to retain more semantic information to generate *** model was applied to species in Southern California,USA,citing SWOT analysis data to train the *** show that the model is capable of integrating data from more comprehensive analyses than traditional methods and generating high-quality reconstructed data from them,effectively solving the problem of insufficient data collection in development *** model is further validated by the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)classification assessment commonly used in the environmental data *** study provides a reliable and rich source of training data for species introduction site selection systems and makes a significant contribution to ecological and sustainable development.

关键词： Convolutional Neural Network(CNN) VAE GAN TOPSIS data reconstruction